The field of the disclosure relates generally to data filtering, and more specifically, to methods and systems for spatial filtering using a stochastic sparse tree grid.
One problem with existing data filtration solutions is that such solutions cannot manage extremely large sets of data where the signals of interest lie within a large set of unimportant data. This problem is sometimes referred to as a noise and interference cancellation problem. More specifically, existing data filtration solutions to the noise and interference cancellation problem for wide area sensors must simplify their processing when trying to spatially match information from frame to frame due to, in the two dimensional case, the O(N2M2) complexity of matching location information across an N×M grid. This simplification in processing results in an artificial reduction of N, M or a reduction in matching with other information from all parts of the grid. Currently, the only way to overcome this computational problem is to increase the computational resources associated with the sensor beyond what would be practical to have within such sensor systems.